Triple
T21662056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Market hall of Montbrison |
E534617
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Montbrison |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Montbrison | Statement: [Market hall of Montbrison, locatedIn, Montbrison]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Montbrison Context triple: [Market hall of Montbrison, locatedIn, Montbrison]
-
A.
Montbrison
chosen
Montbrison is a historic town in central France known as a former capital of the Forez region and for its medieval heritage and regional gastronomy.
-
B.
Mouterhouse
Mouterhouse is a small rural commune in northeastern France, situated in the Moselle department within the Grand Est region.
-
C.
Holimont
Holimont is a private ski resort in Western New York known for its family-oriented atmosphere and well-groomed slopes.
-
D.
Montfaucon
Montfaucon is a small municipality in the Jura canton of Switzerland, situated on the Franches-Montagnes plateau.
-
E.
Mount Blue
Mount Blue is a prominent forested peak in western Maine known for its hiking trails, scenic views, and location within Mount Blue State Park.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e0c467e1f48190af2650b19175abc4 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef6c0883d481908dfdc66832c34d74 |
completed | April 27, 2026, 2 p.m. |
Created at: April 16, 2026, 6:36 p.m.